Clinical mass spectrometry in neuroscience. Proteomics and peptidomics.

In this review we discuss the merits and drawbacks with the use of proteomic and peptidomic strategies for identification of proteins and peptides in their multidimensional interactions in complex biological processes. The progress in proteomics and peptidomics during the last years offer us new challenges to study changes in the protein and peptide synthesis. These strategies also offer new tools to follow post-translational modifications and other disturbed chemical processes that may be indicative of pathophysiological alteration(s). Furthermore these techniques can contribute to improvements in the diagnosis and therapy of neurodegenerative diseases, such as Alzheimer's disease, and psychiatric diseases, as depression and post traumatic stress disorders. We also consider different practical aspects of the applications of mass spectrometry in clinical neuroscience, illustrated by example from our laboratories. The new proteomic and peptidomic strategies will further enable the progress for clinical neuroscience research.     

Proteomics in thyroid cancer and other thyroid-related diseases: A review of the literature

Misdiagnosis, over-diagnosis, or inappropriate treatment strategies are frequently seen in thyroid disease management. Currently, there is an urgent interest to identify biomarkers for specific disease states in the thyroid gland. Proteomics-based approaches have been widely used for the discovery of potential biomarkers in thyroid research. Specifically, proteomic techniques have been used to better understand thyroid tumors of different origin and classification. Besides, there is remarkable thyroid proteomics research in thyroid-related diseases, including thyroid orbitopathy. In this review, we aim to describe proteomic studies and how the results obtained from thyroid cancer, up to now, as well as those from, other thyroid-related diseases pose challenges, which might be solved via high-resolution protein analysis.     

Proteomic Approaches to Decipher Mechanisms Underlying Pathogenesis in Multiple Sclerosis Patients

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system (CNS). The cause of MS is unknown, with no effective therapies available to halt the progressive neurological disability. Development of new and improvement of existing therapeutic strategies therefore require a better understanding of MS pathogenesis, especially during the progressive phase of the disease. This can be achieved through development of biomarkers that can help to identify disease pathophysiology and monitor disease progression. Proteomics is a powerful and promising tool to accelerate biomarker detection and contribute to novel therapeutics. In this review, an overview of how proteomic technology using CNS tissues and biofluids from MS patients has provided important clues to the pathogenesis of MS is provided. Current publications, pitfalls, as well as directions of future research involving proteomic approaches to understand the pathogenesis of MS are discussed.     

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.     

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.     

Poxvirus Proteomics and Virus-Host Protein Interactions

Summary: Studies of the functional proteins encoded by the poxvirus genome provide information about the composition of the virus as well as individual virus-virus protein and virus-host protein interactions, which provides insight into viral pathogenesis and drug discovery. Widely used proteomic techniques to identify and characterize specific protein-protein interactions include yeast two-hybrid studies and coimmunoprecipitations. Recently, various mass spectrometry techniques have been employed to identify viral protein components of larger complexes. These methods, combined with structural studies, can provide new information about the putative functions of viral proteins as well as insights into virus-host interaction dynamics. For viral proteins of unknown function, identification of either viral or host binding partners provides clues about their putative function. In this review, we discuss poxvirus proteomics, including the use of proteomic methodologies to identify viral components and virus-host protein interactions. High-throughput global protein expression studies using protein chip technology as well as new methods for validating putative protein-protein interactions are also discussed.     

Clinical Proteomics and OMICS clues useful in Translational Medicine Research

ABSTRACT: Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been used to identify distinctive molecular signatures in a wide array of biological systems, spanning areas of basic biological research, clinical diagnostics, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomic approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures, specific for multiple diseases, including cancer and pre-invasive lesions, are emerging. This article combines, in a simple manner, relevant proteomic and OMICS clues used in the discovery and development of diagnostic and prognostic biomarkers that are applicable to all clinical fields, thus helping to improve applications of clinical proteomic strategies for translational medicine research.     

Genomics and clinical medicine: rationale for creating and effectively evaluating animal models

Because resolving human complex diseases is difficult, appropriate biomedical models must be developed and validated. In the past, researchers have studied diseases either by characterizing a human clinical disease and choosing the most appropriate animal model, or by characterizing a naturally occurring or induced mutant animal and identifying which human disease it best resembled. Although there has been a great deal of progress through the use of these methods, such models have intrinsic faults that limit their relevance to clinical medicine. The recent advent of techniques in molecular biology, genomics, transgenesis, and cloning furnishes investigators with the ability to study vertebrates (e.g., pigs, cows, chickens, dogs) with greater precision and utilize them as model organisms. Comparative and functional genomics and proteomics provide effective approaches for identifying the genetic and environmental factors responsible for complex diseases and in the development of prevention and treatment strategies and therapeutics. By identifying and studying homologous genes across species, researchers are able to accurately translate and apply experimental data from animal experiments to humans. This review supports the hypothesis that associated enabling technologies can be used to create, de novo, appropriate animal models that recapitulate the human clinical manifestation. Comparative and functional genomic and proteomic techniques can then be used to identify gene and protein functions and the interactions responsible for disease phenotypes, which aids in the development of prevention and treatment strategies.     

Computational methods for protein identification from mass spectrometry data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.     

Proteomic analysis of lymphoid and haematopoietic neoplasms: There's more than biomarker discovery

Lymphoid and haematopoietic neoplasms comprise a broad spectrum of different tumours, classified by the World Health Organization (WHO) on the basis of a combination of morphology, immunophenotypic, genetic and clinical features. Up to date for many of these neoplasms no single feature is regarded as a diagnostic gold standard.The application of proteomics to the study of neoplastic haematological diseases could help in the search for new diagnostic and prognostic markers, as well as in the development of new therapeutic strategies. In this review, we focus on the actual role of proteomics technologies in the study of neoplastic haematology. In particular, we analyse the results obtained in the field of body fluid, cell lines, and tissues proteomics, and discuss the improvement allowed by the new developed proteomic strategies, such as nanofluidic systems, analysis of formalin-fixed tissues, and quantitative high throughput techniques (SILAC, ICAT, iTRAQ).     

Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective

Vascular proteomics is providing two main types of data: proteins that actively participate in vascular pathophysiological processes and novel protein candidates that can potentially serve as useful clinical biomarkers. Although both types of proteins can be identified by similar proteomic strategies and methods, it is important to clearly distinguish biomarkers from mediators of disease. A particular protein, or group of proteins, may participate in a pathogenic process but not serve as an effective biomarker. Alternatively, a useful biomarker may not mediate pathogenic pathways associated with disease (i.e., C-reactive protein). To date, there are no clear successful examples in which discovery proteomics has led to a novel useful clinical biomarker in cardiovascular diseases. Nevertheless, new sources of biomarkers are being explored (i.e., secretomes, circulating cells, exosomes and microparticles), an increasing number of novel proteins involved in atherogenesis are constantly described, and new technologies and analytical strategies (i.e., quantitative proteomics) are being developed to access low abundant proteins. Therefore, this presages a new era of discovery and a further step in the practical application to diagnosis, prognosis and early action by medical treatment of cardiovascular diseases.     

Proteomics for biodefense applications: progress and opportunities

The increasing threat of bioterrorism and continued emergence of new infectious diseases has driven a major resurgence in biomedical research efforts to develop improved treatments, diagnostics and vaccines, as well as increase the fundamental understanding of the host immune response to infectious agents. The availability of multiple mass spectrometry platforms combined with multidimensional separation technologies and microbial genomic databases provides an unprecedented opportunity to develop these much needed resources. An overview of current proteomic strategies applied to microbes and viruses considered potential bioterrorism agents is presented. The emerging area of immunoproteomics as applied to the development of new vaccine targets is also summarized. These powerful research approaches can generate a multitude of potential new protein targets; however, translating these proteomic discoveries to useful counter-bioterrorism products will require large collaborative research efforts across multiple basic science and clinical disciplines. A translational proteomic research paradigm illustrating this approach using influenza virus as an example is discussed.     

Proteomics for biodefense applications: progress and opportunities

The increasing threat of bioterrorism and continued emergence of new infectious diseases has driven a major resurgence in biomedical research efforts to develop improved treatments, diagnostics and vaccines, as well as increase the fundamental understanding of the host immune response to infectious agents. The availability of multiple mass spectrometry platforms combined with multidimensional separation technologies and microbial genomic databases provides an unprecedented opportunity to develop these much needed resources. An overview of current proteomic strategies applied to microbes and viruses considered potential bioterrorism agents is presented. The emerging area of immunoproteomics as applied to the development of new vaccine targets is also summarized. These powerful research approaches can generate a multitude of potential new protein targets; however, translating these proteomic discoveries to useful counter-bioterrorism products will require large collaborative research efforts across multiple basic science and clinical disciplines. A translational proteomic research paradigm illustrating this approach using influenza virus as an example is discussed.     

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.     

High pressure, an alternative approach to understand protein misfolding diseases.

Protein folding is essential for the flow of genetic information to biological activity. A failure in this process can result in disease, by causing cell damage and sometimes death. The misfolding of proteins often induces their aggregation, initiating the fibril formation seen in a range of human and animal diseases. Because misfolding and aggregation are of fundamental importance in vivo, there is currently great interest in understanding their mechanisms. To gain insight into the folding and unfolding processes of proteins, for nearly a century, an original biophysical approach has been successfully used: the application of high hydrostatic pressure combined with various spectroscopic and kinetic techniques. Because high pressure provides new insight into protein structure and folding which cannot be obtained by other techniques, the conformations of pressure-induced unfolding intermediates and species involved in the initial states of aggregation of proteins associated with specific diseases are currently being investigated. Our contention is that by exploring folding kinetics, misfolding pathways and stability under pressure, it will be possible to understand the mechanisms of amyloidogenesis, with the ultimate goal to design therapeutic strategies to prevent progression of the disease.     

定量蛋白质组学在急性高原病研究中的应用进展

急性高原病(acute mountain sickness,AMS)是人体急性暴露于高原低压低氧环境后出现多系统生理紊乱的临床综合征。定量蛋白质组学技术可以系统定量并描述机体蛋白质组成和动态变化规律,近年来在多种疾病的预防、诊断、治疗和发生机制等方面研究应用广泛。本文系统综述了定量蛋白质组学技术及其在AMS的预防、诊断、治疗和急进高原习服机制研究中的应用进展,以期为AMS的发病机制、提前干预、临床治疗和AMS的蛋白质组学研究提供参考。     

After genomics,what proteomics tools could help us understand the antimicrobial resistance of Escherichia coli?

Proteomic approaches have been considerably improved during the past decade and have been used to investigate the differences in protein expression profiles of cells grown under a broad spectrum of growth conditions and with different stress factors including antibiotics. In Europe, the most significant disease threat remains the presence of microorganisms that have become resistant to antimicrobials and so it is important that different scientific tools are combined to achieve the largest amount of knowledge in this area of expertise. The emergence and spread of the antibiotic-resistant Gram-negative pathogens, such as Escherichia coli, can lead to serious problem public health in humans. E. coli, a very well described prokaryote, has served as a model organism for several biological and biotechnological studies increasingly so since the completion of the E. coli genome-sequencing project. The purpose of this review is to present an overview of the different proteomic approaches to antimicrobial-resistant E. coli that will be helpful to obtain a better knowledge of the antibiotic-resistant mechanism(s). This can also aid to understand the molecular determinants involved with pathogenesis, which is essential for the development of effective strategies to combat infection and to reveal new therapeutic targets. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.